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In the construction process, it is always important to know the concrete compressive strength. The recommended procedure to ensure the concrete strength is to perform cylinder test. Test result of concrete
cylinder at 28th day, represents the characteristic strength of the concrete that has been prepared and cast to form the concrete work. Usually...
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... mix design method (ACI 211.1-91) was used for the mix design process and for testing the cylinders ASTM (ASTM C39) recommendation was used. Out of 56 sample data sets, randomly selected 20 sample data sets are shown in Table 1. Ranges of material properties and concrete strengths achieved for all the 56 data sets are shown in Table 2. ...
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Citations
... Compressive strength testing is an overall assessment of mortar performance [23]. This parameter is determined by many factors, such as the amount of water, cement, various additives, and their proportions [24]. ...
Innovative building materials should also be pro-environmental. This article discusses the environmental footprint of geopolymer and cement-based mortars. It describes the methodology for preparing geopolymer and cement mortars using mineral wool waste. The phenol–formaldehyde resin used in mineral wool is a source of phenol and formaldehyde emissions to the environment. The prepared mortar samples were subjected to durability tests to assess the correlation between the amount of mineral wool and the flexural and compressive strength of the samples. The key element of the paper is to test whether immobilisation of mineral wool in the geopolymer will reduce leaching of phenol and formaldehyde into the environment. The results revealed that cements prepared with mineral wool showed higher compressive strength, whereas geopolymer samples had better flexural strength. The study also proved that immobilisation of the wool in the geopolymer reduces phenol and formaldehyde leaching significantly.
... times the compressive modulus in the first week of the material. Hasan and Kabir [6] developed a reasonable polynomial mathematical model to predict the compressive strength of concrete at 28 days, based on early results. Peng et al. [7] proposed an improved hyperbolic model to predict the compressive strength of the early-age concrete. ...
... Traditionally, the linear regression analysis is based on the least-square solution. Letting Table 3 into Equation (2) (6) Note that the values in Equations (4) and (5) are from Table 3, that and the corresponding units are kPa. In Equation (6), Table 4. ...
Few studies have reported the cohesion and friction angle of concrete at a super early age. However, these two mechanical parameters are necessary to study the influence of engineering vibration on super-early-age concrete. In view of this, the mechanical properties of the super-early age-concrete are investigated in this work by direct shear testing. Firstly, the shear strength of the super-early-age concrete is measured by the direct shear experiment under different normal pressures at different times. Secondly, the cohesion and friction angle of the super early age concrete are calculated according to the Mohr–Coulomb criterion of failure. To overcome the great discreteness and randomness in the measured data, a new robust regression analysis algorithm is presented to replace the traditional regression analysis method to obtain more reliable and reasonable mechanical parameters. According to the experimental and theoretical analysis results, it is found that the friction angles of the super early age concrete are located in the interval of [50°, 70°]. The cohesion of the concrete is about 78.7 kPa at the initial setting state and about 190.9 kPa at the final setting state, respectively. It has been shown that the cohesion of the concrete at a super-early age tends to increase rapidly with time. The method and test results of this work can be used as a reference for relevant engineering practice. Specifically, the proposed regression method can be extended to the data analysis of other mechanical parameters of concrete, as well as other brittle materials such as rock. The test results of early concrete cohesion and friction angle can be used to analyze the adverse effects of vibration on newly cast concrete members in pile driving and blasting engineering.
... The effect was more pronounced for 50 mm diameter cores drilled from concrete having lower strength. [9]. Hasan & Kabir (2011) proposed a study to predict the compressive strength of concrete from early age result. ...
... [9]. Hasan & Kabir (2011) proposed a study to predict the compressive strength of concrete from early age result. The study to develop a simple mathematical model based on concrete's nature of strength gain to predict the compressive strength of concrete at 28th day from early age results, i.e., 3-days or 7-days test results. ...
Concrete core test is a semi-destructive test, conducted to ascertain the in- situ strength of the hardened concrete of a structure. In such case it is desired to extract cores without reinforcement. If the reinforcements are present in the core, then the core strength does not mean the compressive strength of concrete in the structure from which the core was extracted. The objective of this study was to study the effect of orientation of reinforcement on the compressive strength of concrete core. 10 mm and 12 mm reinforcement were embedded in the test specimens. A set of cores containing different orientations of reinforcement were extracted. The test results indicate that the presence of reinforcement of diameter 12 mm reduces the strength of concrete core from 3% to 30%, while the reinforcement of diameter 10 mm reduces the strength of concrete core from 5% to 36%. The bond between the reinforcement and the core gets affected during the coring action due to which the strength gets reduced in a reinforced core. The reduction of strength of an unreinforced core ranges around 40% when compared to the cube compressive strength. An empirical relationship with several factors influencing the core compressive strength is formulated and the same is validated.
... The betterunderstanding of the structure and behavior of concrete at micro-scale could help to improve concrete properties and make concrete more durable [13]. Characteristics like, durability, impermeability and volume stability may be important in some case of designing concrete structure but strength is the most important one since an overall picture of concrete quality is being reflected by the concrete strength [14]. ...
... To further enhance the properties of concrete, several chemical or mineral admixtures such as fly ash, blast furnace slag, silica fume, metakaolin, and superplasticizer could be added into the mixture. Compressive strength is the most important factor that reflects the quality of a concrete mix design [8]. e concrete compressive strength is usually characterized by estimating the values at 28 days. ...
... Besides, the compressive strength of concrete also depends on the content and nature of the mix design, the curing condition, and the age of specimens [10][11][12]. Apart from Abrams' law, Hasan and Kabir [8] and ACI 209-71 [13] have proposed empirical equations to determine the compressive strength of concrete at any age (Table 1). However, the empirical methods could not take into account all factors that affect the concrete compressive strength, such as supplementary cementitious materials or the mixture components. ...
... Summary of the empirical equations for determining the compressive strength of concrete. compressive strength; A, B: constant; W/C: water/cement ratio No Hasan and Kabir[8] S t n � (pD n /(D n + q)) p, q: constant; n: day; D n : number of days Yes ACI 209-71[13] S t n � (t/(a + bt))S 28d a, b: constant; t: number of days; S 28d : compressive strength at 28 days Yes ...
Accurate prediction of the concrete compressive strength is an important task that helps to avoid costly and time-consuming experiments. Notably, the determination of the later-age concrete compressive strength is more difficult due to the time required to perform experiments. Therefore, predicting the compressive strength of later-age concrete is crucial in specific applications. In this investigation, an approach using a feedforward neural network (FNN) machine learning algorithm was proposed to predict the compressive strength of later-age concrete. The proposed model was fully evaluated in terms of performance and prediction capability over statistical results of 1000 simulations under a random sampling effect. The results showed that the proposed algorithm was an excellent predictor and might be useful for engineers to avoid time-consuming experiments with the statistical performance indicators, namely, the Pearson correlation coefficient (R), root-mean-squared error (RMSE), and mean squared error (MAE) for the training and testing parts of 0.9861, 2.1501, 1.5650 and 0.9792, 2.8510, 2.1361, respectively. The results also indicated that the FNN model was superior to classical machine learning algorithms such as random forest and Gaussian process regression, as well as empirical formulations proposed in the literature.
... The ANN modelling philosophy is similar to a number of conventional statistical models in the sense that both are attempting to capture the relationship between a historical set of model inputs and corresponding outputs (Shain et al., 2001). (Chopra et al., 2015) Unlike conventional problem solving algorithms that are basically based upon statistical analysis by which many linear and nonlinear regression equations have been constructed to model such a prediction problem (Monjurul and Ahsanul, 2011), Artificial Neural Network can be trained to perform a particular task. This is done by presenting the system with a representative set of examples describing the problem, namely pairs of input and output samples. ...
Compressive strength of concrete at the age of 28 days is an important parameter for the design of concrete structures and waiting for that length of time to obtain the value can be tasky. This study developed an alternative approach using Artificial Neutral Network (ANN) to estimate or predict the compressive strength of concrete at 28th day from early age results. In the study concrete cubes of mix ratio 1:2:4 were cast with different water-cement ratios (0.4, 0.5, 0.6 and 0.65) and their seventh (7th) and twenty-eighth (28th) day strength were measured in the laboratory. In all, 400 cubes of 150 x 150 x 150mm of 200 sets were subjected to compressive strength test using Avery Denison Universal Testing Machine of 2000 kN load capacity at a constant load application of 15kN/s. ANN model was then developed using the time series tool of ANN in MATLAB 7.12.0 (R2011a) applying back propagation algorithm. Out of the 200 sets of results, 110 sets (55%) were used for the training of the network while 30 sets (15%) were used to validate and 60 sets (30%) to test the network. The result of the crushing test shows that the higher the compressive strength at seventh (7th) day the higher it will be at twenty-eighth (28th) day. The result of the ANN model shows a good correlation between the seventh (7th) day compressive strength and the twenty-eighth (28th) day compressive strength with training and validation correlation coefficients of 0.99751 and 0.99736 respectively. It was also found that the ANN model u 쳌䁐䀀㌳㌳ Ͷ䁐䀀Ͷⷸ is quite efficient in determining the twenty-eighth (28th) day compressive strength of concreteas the predicted strength values match very well with those obtained experimentally with a correlation coefficient of 0.99675.
... discrepancy between the estimation model and data set using below Eq. 10. The smaller residual sum of square values shows a goodness of fit of the model to the data [54]. ...
Rapid repair and retrofit of existing infrastructures demand durable high early strength materials that not only deliver sufficient strength within a short time after placement but also significantly prolong the maintenance interval. This research paper presents the effects on the mechanical properties and durability of alccofine concrete of the addition of calcium nitrate as a non-chloride hardening accelerator (NCHA). Non-chloride accelerator with concentrations of 0.65%, 0.85% and 1.05% by weight of cement, was added to concrete mixes to test the effect on the properties of alccofine concrete which was in turn compared with the reference concrete without NCHA. With addition of accelerator, strength enhancements were observed at an early age due to rapid rate of hydration of C3A and C3S phases. Water absorption and sulphate resistance of alccofine concrete also improved with the non-chloride accelerator. A statistical tool was used to predict the experimental values of compressive strength of concrete. Response surface methodology was adopted to optimize the experimental data set in which regression equation was developed by relating response variable to input variable. This method helped to predict the experimental values within an acceptable error range. The predicted values were cross validated by employing coefficient of determination (R²) and residual sum of squares (RSS) which showed a good fit. The results of this study showed that the addition of non-chloride hardening accelerator in alccofine concrete significantly improved the mechanical properties as well as durability.
... Soroushian and Elzafraney (2004) studied the damage caused by compression, impact, fatigue and the freeze-thaw cycle on ordinary concrete and high-performance concrete as well as the damage effects on concrete properties, such as bending strength, impact strength, permeability and crack propagation degree. Hasan and Kabir (2011) and Sukumar et al. (2008) proposed the corresponding prediction models based on the mechanical properties of early-age concrete and predicted the mechanical properties of late-age concrete. Beushausen et al. (2012) studied the impact of different water/cement ratios and different slag substitutes on strength development of early-age concrete. ...
As the depth of mines increases, the in situ stress increases gradually, resulting in increasingly demanding requirements for the support strength of coal-mine roadways and making it more difficult to provide this support. For this reason, more effective forms of support are needed. Concrete is a typical support form, but ordinary concrete has low support strength, cracks easily and is prone to brittle failure, whereas polypropylene fibre-reinforced concrete has a good inhibition effect on crack propagation and can remarkably improve the post-cracking performance and toughness of concrete. This paper studies the mechanical properties and application effects of wet-sprayed polypropylene fibre concrete in the mining context. A final mix proportion is obtained, a flexural toughness test on the round slabs of the concrete is conducted, and the corresponding initial cracking strength, peak strength, fracture energy and toughness are studied. This wet-sprayed polypropylene fibre concrete was applied and its application effect investigated. The results show that wet-sprayed polypropylene fibre concrete has advantages such as enhanced integrity and more uniform stress distribution. The initial cracking strength, peak load and energy absorbed of wet-sprayed polypropylene fibre concrete specimens are higher than those of dry-sprayed reinforcing mesh concrete specimens. An engineering practice application indicates that the resilience rate and dust concentration were significantly reduced during wet-sprayed polypropylene fibre concrete construction, and construction efficiency and economic benefits clearly increased. The research achievements are of great theoretical and practical significance in developing a further understanding of the fracture instability mechanism and mechanical properties of wet-sprayed polypropylene fibre concrete. This method may be applied widely in sinking and driving engineering to improve the support effect and ensure mine safety.
... RSM offers several advantages for optimization over the one factor at a time approach which is tedious and also does not take into account the interaction of factors [25]. RSM proportions the constituent material to obtain an optimum mix proportions used as a mathematical model for the prediction of the desired properties [26]. ...
This study showcases the predictive and optimization capabilities of response surface methodology with respect to the fresh and hardened properties of waste tyre steel fibre reinforced concrete containing limestone powder. Response surface methodology has the advantage of simultaneously varying chosen independent variables to provide a useful model for overall response variation. The study identifies aspect ratio (50–140), water cement ratio (0.2–0.4) and cement content (25%–40%) as independent variables while limestone powder was kept constant at 5% by weight of concrete. Predictive equations for the water intake/absorption, compressive strength, flexural strength, split tensile strength and slump of fibre reinforced concrete were obtained using the independent variables. The analysis of variance (ANOVA) for all properties indicates that the modified quadratic model was able to effectively predict the fresh and hardened properties of fibre reinforced concrete with coefficient of determination ranging between 0.86 and 0.98. In addition, RSM model predictive efficiency was classified as very good for compressive strength, splitting tensile strength, slump and water absorption and acceptable for FS in terms of Nash & Sutcliffe coefficient of model efficiency. An optimum condition of 140 for the aspect ratio, 0.26 for water cement ratio and 40% for cement content corresponding to 0.94%, 42.69 N/mm², 7.97 N/mm² 5.23 N/mm² 7.65 cm for water intake/absorption, compressive strength, flexural strength, split tensile strength and slump respectively was achieved. These predictions were validated and a good correlation was observed between the experimental and predicted values judging by the absolute relative percent error of 0.842, 11.35, 3.6, 18.22 and 2.04 for water intake/absorption, compressive strength, flexural strength, split tensile strength and slump respectively. The proposed mathematical models are capable of predicting the required fresh and hardened properties of fibre-reinforced concrete as to inform early decision making when utilized in construction.
... Response surface method (RSM) opens new possibilities in the classification and generalization of available experimental results to estimate concrete strength from the mix components. This work presents and examines the mix proportioning of ordinary concrete using RSM technique to optimize the mixture proportions and development of mathematical model for desired properties of concrete compressive strength in terms predictable and increase the efficiency of the prediction [1]. ...
Response Surface Methods (RSM) provide statistically validated predictive models that can then be manipulated for finding optimal process configurations. Variation transmitted to responses from poorly controlled process factors can be accounted for by the mathematical technique of propagation of error (POE), which facilitates 'finding the flats' on the surfaces generated by RSM. The dual response approach to RSM captures the standard deviation of the output as well as the average. It accounts for unknown sources of variation. Dual response plus propagation of error (POE) provides a more useful model of overall response variation. In our case, we implemented this technique in predicting compressive strength of concrete of 28 days in age. Since 28 days is quite time consuming, while it is important to ensure the quality control process. This paper investigates the potential of using design of experiments (DOE-RSM) to predict the compressive strength of concrete at 28th day. Data used for this study was carried out from experiment schemes at university of Benghazi, civil engineering department. A total of 114 sets of data were implemented. ACI mix design method was utilized for the mix design. No admixtures were used, only the main concrete mix constituents such as cement, coarse-aggregate, fine aggregate and water were utilized in all mixes. Different mix proportions of the ingredients and different water cement ratio were used. The proposed mathematical models are capable of predicting the required concrete compressive strength of concrete from early ages.
